Number Of Frequency Bands Research Articles

Eigenimage2Eigenimage (E2E): A Self-Supervised Deep Learning Network for Hyperspectral Image Denoising.

The performance of deep learning-based denoisers highly depends on the quantity and quality of training data. However, paired noisy-clean training images are generally unavailable in hyperspectral remote sensing areas. To solve this problem, this work resorts to the self-supervised learning technique, where our proposed model can train itself to learn one part of noisy input from another part of noisy input. We study a general hyperspectral image (HSI) denoising framework, called Eigenimage2Eigenimage (E2E), which turns the HSI denoising problem into an eigenimage (i.e., the subspace representation coefficients of the HSI) denoising problem and proposes a learning strategy to generate noisy-noisy paired training eigenimages from noisy eigenimages. Consequently, the E2E denoising framework can be trained without clean data and applied to denoise HSIs without the constraint with the number of frequency bands. Experimental results are provided to demonstrate the performance of the proposed method that is better than the other existing deep learning methods for denoising HSIs. A MATLAB demo of this work is available at https://github.com/LinaZhuang/HSI-denoiser-Eigenimage2Eigenimage for the sake of reproducibility.

Analysis of the Variation in Bearing Estimation Error with Frequency Bands for a Source Beneath the Arctic Ice Using a Geophone

To obtain better frequency bands for source bearing estimation, experiments using an ice-mounted geophone were performed at three sites on the Arctic ice cap. By transforming to the frequency domain, errors of the bearing estimation in a number of frequency bands within 1000 Hz and the horizontal peak displacements received by the geophone in the corresponding frequency bands were obtained. After comparing the variation in errors to the peak displacements in the same frequency band, it was found that the errors are related to the peak displacements, and higher peak displacement values mean smaller errors. When the incident angle of the acoustic source and the ice thickness meet certain conditions, some modes of the Lamb waves of the ice plate are excited, the peak displacements in the same frequency band are increased, the errors of bearing estimation are reduced, and the effective frequency band for bearing estimation is broadened. These results provide some new ideas for the bearing estimation of acoustic sources beneath the Arctic ice.

Quadband Petal Reflector Antenna for Ground Communications: Combining four frequency bands into one innovative and reliable design

Future protected communications require soldiers on the ground to carry several antennas integrated with their manpacks to provide secure and reliable communications at a number of frequency bands. This article describes a novel quadband petal reflector antenna (QPRA) that combines four frequency bands into one using a quadruplexer. A dual-reflector antenna utilizing an axially displaced ellipsoid subreflector being fed with a quad-ridged horn provides communications at Ku-band transmit (Ku-Tx), Ku-band receive (Ku-Rx), K-band receive (K-Rx), and Ka-band transmit (Ka-Tx) frequencies simultaneously. The main reflector is made of six identical petals that can be quickly assembled and disassembled in the battlefield. The antenna is mounted on a lightweight gimbal to provide beam scanning over a hemispherical coverage. The antenna is mounted on a tripod structure for field operations and uses commercial off the shelf (COTS) components and 3D manufactured parts to minimize cost and mass. The novelty of the antenna presented in this article includes a wide bandwidth capability of 73%, the use of a petal reflector, a 3D manufactured quad-ridged horn, a high-performance quadruplexer, and the use of COTS gimbals for beam scanning. Antenna design, analyses, hardware, and test results are presented in this article. The measured results of the antenna agree well with the computed results validating the QPRA design.

Multi frequency band fusion method for EEG signal classification

This paper proposes a novel convolutional neural network (CNN) fusion method for electroencephalography (EEG) motor imagery (MI) signal classification. The method is named MFBF, which stands for multifrequency band fusion. The MFBF method relies on filtering the input signal with different frequency bands and feeding each band signal to a duplicate of a CNN model; then, all duplicates are concatenated to form a fusion model. This paper also introduces the second release of Coleeg software, which is used for evaluation. The MFBF method has the advantage of the flexibility of choosing any model and any number of frequency bands. In the experimental evaluation, the CNN1D model and three frequency bands were used to form the CNN1D_MFBF model, and it was evaluated against the EEGNet_fusion model on three different datasets, which are: Physionet, BCI competition IV-2a, and a dataset from the Hungarian Academy of Sciences Research Centre for Natural Sciences (MTA-TTK). The CNN1D_MFBF model had comparable or better accuracy results with less than one-fifth of the training time, which is a significant advantage for the proposed method.

Minkowski-like fractal seismic metamaterial with wide low-frequency band gaps on single and layered soil

In this paper, we propose a resource-efficient Minkowski-like fractal seismic metamaterial by hybridizing U-shaped and cross-shaped pillars, providing wide complete band gaps (BGs) due to its multi-scale self-similar property. Numerical modeling of seismic surface waves is used to study the band structure and transmission of our seismic metamaterial. A comparison of the band structures of the developed seismic metamaterial with various levels reveals that the iteration order itself is responsible for the increase in the number of frequency bands and the decrease in the center frequencies of the BGs. Furthermore, the vibrational modes are calculated and examined to understand the mechanism of BG generation. To demonstrate the efficiency of earthquake shielding in multiple complete BGs, investigations of seismic surface wave propagation on a 1D array of Minkowski-like fractal structure units on the surface of single and layered semi-infinite substrates are employed. The results show that the layered soil has the function of widening BGs by itself. Our proposed Minkowski-like fractal structure due to its multi-scale self-similarity mitigates the intrinsic drawback of the narrow BG of resonant metamaterial, providing a superior alternative in seismology and related areas of multi-frequency band vibration reduction. Moreover, its green design and manufacturing due to low filling rates, strong wear resistance, and ductility can realize the low-carbon and sustainable development of the construction industry.

Personalization of Hearing Aid Fitting Based on Adaptive Dynamic Range Optimization.

Adaptive dynamic range optimization (ADRO) is a hearing aid fitting rationale which involves adjusting the gains in a number of frequency bands by using a series of rules. The rules reflect the comparison of the estimated percentile occurrences of the sound levels with the audibility and comfort hearing levels of a person suffering from hearing loss. In the study reported in this paper, a previously developed machine learning method was utilized to personalize the ADRO fitting in order to provide an improved hearing experience as compared to the standard ADRO hearing aid fitting. The personalization was carried out based on the user preference model within the framework of maximum likelihood inverse reinforcement learning. The testing of ten subjects with hearing loss was conducted, which indicated that the personalized ADRO was preferred over the standard ADRO on average by about 10 times. Furthermore, a word recognition experiment was conducted, which showed that the personalized ADRO had no adverse impact on speech understanding as compared to the standard ADRO.

Auditory grouping is necessary to understand interrupted mosaic speech stimuli.

The intelligibility of interrupted speech stimuli has been known to be almost perfect when segment duration is shorter than 80 ms, which means that the interrupted segments are perceptually organized into a coherent stream under this condition. However, why listeners can successfully group the interrupted segments into a coherent stream has been largely unknown. Here, we show that the intelligibility for mosaic speech in which original speech was segmented in frequency and time and noise-vocoded with the average power in each unit was largely reduced by periodical interruption. At the same time, the intelligibility could be recovered by promoting auditory grouping of the interrupted segments by stretching the segments up to 40 ms and reducing the gaps, provided that the number of frequency bands was enough () and the original segment duration was equal to or less than 40 ms. The interruption was devastating for mosaic speech stimuli, very likely because the deprivation of periodicity and temporal fine structure with mosaicking prevented successful auditory grouping for the interrupted segments.

Signal envelope and speech intelligibility differentially impact auditory motion perception

Our acoustic environment contains a plethora of complex sounds that are often in motion. To gauge approaching danger and communicate effectively, listeners need to localize and identify sounds, which includes determining sound motion. This study addresses which acoustic cues impact listeners’ ability to determine sound motion. Signal envelope (ENV) cues are implicated in both sound motion tracking and stimulus intelligibility, suggesting that these processes could be competing for sound processing resources. We created auditory chimaera from speech and noise stimuli and varied the number of frequency bands, effectively manipulating speech intelligibility. Normal-hearing adults were presented with stationary or moving chimaeras and reported perceived sound motion and content. Results show that sensitivity to sound motion is not affected by speech intelligibility, but shows a clear difference for original noise and speech stimuli. Further, acoustic chimaera with speech-like ENVs which had intelligible content induced a strong bias in listeners to report sounds as stationary. Increasing stimulus intelligibility systematically increased that bias and removing intelligible content reduced it, suggesting that sound content may be prioritized over sound motion. These findings suggest that sound motion processing in the auditory system can be biased by acoustic parameters related to speech intelligibility.

Teasing apart trauma: neural oscillations differentiate individual cases of mild traumatic brain injury from post-traumatic stress disorder even when symptoms overlap

Post-traumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI) are highly prevalent and closely related disorders. Affected individuals often exhibit substantially overlapping symptomatology – a major challenge for differential diagnosis in both military and civilian contexts. According to our symptom assessment, the PTSD group exhibited comparable levels of concussion symptoms and severity to the mTBI group. An objective and reliable system to uncover the key neural signatures differentiating these disorders would be an important step towards translational and applied clinical use. Here we explore use of MEG (magnetoencephalography)-multivariate statistical learning analysis in identifying the neural features for differential PTSD/mTBI characterisation. Resting state MEG-derived regional neural activity and coherence (or functional connectivity) across seven canonical neural oscillation frequencies (delta to high gamma) were used. The selected features were consistent and largely confirmatory with previously established neurophysiological markers for the two disorders. For regional power from theta, alpha and high gamma bands, the amygdala, hippocampus and temporal areas were identified. In line with regional activity, additional connections within the occipital, parietal and temporal regions were selected across a number of frequency bands. This study is the first to employ MEG-derived neural features to reliably and differentially stratify the two disorders in a multi-group context. The features from alpha and beta bands exhibited the best classification performance, even in cases where distinction by concussion symptom profiles alone were extremely difficult. We demonstrate the potential of using ‘invisible’ neural indices of brain functioning to understand and differentiate these debilitating conditions.

Edge-Coupled Parasitic Split Ring Resonator based Metamaterial Inspired Low-Cost Diamond Shaped Fractal Antenna for Multiband Wireless Applications

ABSTRACT The metamaterial inspired low-cost diamond-shaped fractal antenna (DSFA) based on edge-coupled (EC) parasitic split ring resonator (SRR) for multiband wireless application is presented and investigated in this manuscript. Initially, three iterations of DSFA are designed and found that second iteration reveals the more number of frequency bands as compared to the other iterations. For proper impedance matching characteristics, partial ground plane has been introduced in the designing of antenna and low-cost FR4 glass epoxy substrate with thickness of 1.6 mm is used with an overall size of 32 × 36 mm2. Further, the EC parasitic SRR is loaded in the geometry of the proposed antenna and compared with the unloaded antenna and noted that the loaded antenna reports the better results in terms of bandwidth and reflection coefficient. The loaded antenna exhibits the maximum bandwidth of 5.68 GHz (1.67–7.34 GHz) and a maximum gain of 8.63 dB at 2.3 GHz and 9.90 dB at 19.9 GHz. The prototype of the proposed DSFA has been fabricated and tested for the authentication of measured results with the simulated results and found both are in agreement with each other. Proposed DSFA with EC parasitic SRR is best suitable for different wireless applications because of its multiband behaviour.

A miniaturized 2-itertion rectangular slotted Sierpinski Fractal Bowtie antenna for multiband applications

Recent advancements in the field of Telecommunications and wireless technology services need compact, multiband antennas with reduced system complexity. In this paper a novel Rectangular slotted Sierpinski Fractal Bowtie antenna is illustrated and is further expanded up to 2-iterations to obtain multi frequency bands with increased percentage of Miniaturization. The overall volume of the proposed 2-iteration SPK Bowtie antenna is (50 × 50 × 1.6) mm3 and the substrate is FR-4 epoxy with 4.4 dielectric constant. All the 0th, 1st and 2nd iterations of Rectangular slotted SPK Fractal Bowtie antenna are exited with coaxial probe feed and are simulated using ANSYS HFSS software for 100 MHz to 14 GHz frequency range. The radiation parameters like return loss, Bandwidth, VSWR, and Gain are evaluated and compared. The simulation results shows that proposed 2nd iteration Rectangular slotted SPK Fractal Bowtie antenna exhibits more number of frequency bands as compared to the 0th and 1st iterations. The proposed design is able to resonate at frequencies 0.2 GHz, 3.5 GHz, 6.3 GHz, 8.6 GHz, 10.9 GHz, 11.7 GHz with a gain of 0.529 dB, 5.074 dB, 4.518 dB, 5.335 dB, 9.18 dB, 21.17 dB respectively. The percentage of Miniaturization is also increased to 58.2% in the case of 2-iteraion. A prototype of the final proposed antenna is fabricated and tested using VNA network analyzer. The fabricated prototype of proposed antenna is also capable of resonating in L, C, S, and X bands. The simulated results of the proposed antenna have a great matching with the measured results.

A test to compare interval time series

We compare two interval time series (ITS) by testing whether their underlying distributions are significantly different or not. To perform hypothesis testing, we make use of the discrete wavelet transform (DWT) which decomposes a time series into a set of coefficients over a number of frequency bands or scales. We obtain the DWT of the radius and centre of each of the two ITS at different scales, and perform randomisation tests. In order to use a randomisation test, the observations must be uncorrelated; this condition is more or less satisfied since at each scale, the DWT coefficients are approximately uncorrelated with each other. Our proposed test statistic is the ratio of the determinants of the covariance matrix of radius and centre DWTs of the two ITS, at each scale. This test statistic ensures that the variability between the upper and lower bounds of each ITS is encompassed. Simulation studies conducted to evaluate the performance of the test show reasonably good estimates of size and power under most conditions, and applications to real interval time series reveal the practical usefulness of this test.

A Theoretical Survey on Patch Antenna for Wideband Communication

Modern communication system is based on wideband communication. A wideband antenna is designed in such a way that it will receive a wide range of frequencies. Microwave frequency spectrum is classified as ranging from 1GHz to 100GHz and this range is divided into a number of frequency bands. These bands are defined as L Band, S Band, C Band, X Band etc. To fulfil the demands of many users patch antenna is designed in these bands. Among different types of antenna, Microstrip Patch Antenna is most popular in wireless communication system. Microstrip patch Antennas have many advantages over other familiar antennas because microstrip patch antennas are of low profile, low cost, low volume, light weight. Low efficiency, low gain and narrow bandwidth of patch antenna create major challenge to a designer. Slots are created on patch for preparing antenna forwideband applications. In this paper, we have surveyed upon various types of Microstrip Patch Antenna, feeding techniques, design equation Substrate Characteristics, Simulation tools etc.

Space-Time-Frequency Multi-Sensor Analysis for Motor Cortex Localization Using Magnetoencephalography.

Brain source imaging and time frequency mapping (TFM) are commonly used in magneto/electro encephalography (M/EEG) imaging. However, these methods suffer from important limitations. Source imaging is based on an ill-posed inverse problem leading to instability of source localization solutions, has a limited capacity to localize high frequency oscillations and loses its robustness for induced responses (ill-defined trigger). The drawback of TFM is that it involves independent analysis of signals from a number of frequency bands, and from co-localized sensors. In the present article, a regression-based multi-sensor space–time–frequency analysis (MSA) approach, which integrates co-localized sensors and/or multi-frequency information, is proposed. To estimate task-specific brain activations, MSA uses cross-validated, shifted, multiple Pearson correlation, calculated from the time–frequency transformed brain signal and the binary signal of stimuli. The results are projected from the sensor space onto the cortical surface. To assess MSA performance, the proposed method was compared to the weighted minimum norm estimate (wMNE) source imaging method, in terms of spatial selectivity and robustness against an ill-defined trigger. Magnetoencephalography (MEG) recordings were performed in fourteen subjects during two motor tasks: finger tapping and elbow flexion/extension. In particular, our results show that the MSA approach provides good localization performance when compared to wMNE and statistically significant improvement of robustness against ill-defined trigger.

Effect of Self-Heating on Terahertz Double Avalanche Region Transit Time Source

This paper highlights the effect of temperature on the high-frequency performance of the double avalanche region avalanche transit time (ATT) source capable of operating in multiple numbers of frequency bands. The variance of static (DC) and large-signal properties on temperature are accounted by utilizing a well-established authors’ developed simulation method. The large-signal admittance characteristics of the source show the presence of discrete and far separated negative conductance bands which can yield a wide tuning capability of it. Here in this paper, linear changes of DC parameters as well as non-linear changes of large-signal parameters with junction temperature have been studied; with the help of utilizing linear and quadratic polynomial curve fitting method, analytical expressions are obtained which represent the DC and high-frequency parameters of the source as functions of junction temperature. These will be very much beneficial for optimization of thermal design-related issues of the ATT sources.

Effect of phoneme variations on blind reverberation time estimation

This study focuses on an unexplored aspect of the performance of algorithms for blind reverberation time (T) estimation – on the effect that speech signal’s phonetic content has on the value of the estimate ofTthat is obtained from the reverberant version of that signal. To this end, the performance of three algorithms is assessed on a set of logatome recordings artificially reverberated with room impulse responses from four rooms, with theirT20value in the [0.18, 0.55] s interval. Analyses of variance showed that the null hypotheses of equal means of estimation errors can be rejected at the significance level of 0.05 for the interaction terms between the factors “vowel”, “consonant”, and “room”, while the results of Tukey’s multiple comparison procedure revealed that there are both some similarities in the behaviour of the algorithms and some differences, where the latter are stemming from the differences in the details of algorithms’ implementation such as the number of frequency bands and whetherTis estimated continuously or only on the selected, the so-called speech decay, segments of the signal.

Multiband Massive Channel Random Access in Ultra-Reliable Low-Latency Communication

Ultra-Reliable Low-Latency Communication (URLLC) is challenging due to its extremely higher reliability requirement with stringent short latency packet transmission. In order to overcome this reliability and latency bound, a communication access scheme needs to assure almost error-free and high speed packet transmission. In this paper, a new multiple-access scheme-Orthogonal Frequency-Subcarrier-based Multiple Access (OFSMA)-is proposed with URLLC's high requirement adaptation. In this scheme, the packet diversity concept is incorporated to achieve the expected packet transmission reliability and a diverse number of the duplicated packet are processed with a set of operations and transmitted over randomly selected orthogonal subcarrier frequency channels. Performances of the OFSMA system are measured in terms of applying several numbers of frequency bands, a massive number of subcarrier channels, a different number of packet duplications, and a diverse rate of traffic arrival conditions. We determined the minimum number of subcarrier channels requirement to satisfy the reliability of 99.999% for different packet duplication in presence of different frequency bands. The reliability response for a fixed number of subcarrier channels is evaluated for different frequency band conditions. Finally, the air interface latency of the OFSMA system is measured for single packet uplink transmission and compared with that of a traditional OFDMA system. The performance results in terms of reliability and latency express that the OFSMA scheme can assure the expected reliability and latency defined by URLLC.

Performance enhancement of nested hexagonal ring‐shaped compact multiband integrated wideband fractal antennas for wireless applications

In this paper, nested hexagonal ring-shaped fractal antennas are designed and investigated which are different from each other in patch orientation. Initially, the multiband integrated wideband hexagonal nested ring antenna is designed (antenna-I). To improve the multiband/wideband behavior, the patch orientation of antenna-I is changed to −60°/60° (antenna-II), −120°/120° (antenna-III), and −180°/180° (antenna-IV). Antennas are designed on low cost FR-4 glass epoxy substrate with relative permittivity of 4.4 and overall dimension 30 × 30 × 1.6 mm3. Comparison among antennas have been made and found that the antennas with negative orientation exhibit better results in terms of bandwidth, impedance matching, number of frequency bands, and gain. Designed antennas have been compared with each other and found that antennas-II and III are better in performance as compared to antennas-I and IV. Antenna-II exhibits wider bandwidth of 1.26 (2.52-3.78 GHz), 2.75 (4.03-6.78 GHz), and 6.1 GHz (7.82-13.92 GHz) with maximum gain of 7.14 dB. Similarly; antenna-III exhibits the bandwidth of 340 MHz (1.92-2.26 GHz), 820 MHz (3.04-3.86 GHz), 4230 MHz (5.38-9.61 GHz), and 3040 MHz (10.41-13.45 GHz) with a maximum gain of 6.19 dB. Prototype of the designed antennas with satisfactory orientations are fabricated and tested for the validation of results. Simulated and measured results are also juxtaposed and observed in good agreement with each other. Antennas exhibit bidirectional and omnidirectional pattern in E-plane and H-plane, respectively, also the radiation efficiency of antennas are in acceptable range from 75% to 95%. Due to the wider bandwidth of designed antennas, they can be used for different wireless standards such as Advance Wireless Services AWS-1, AWS-2, AWS-3, Wi-MAX, WLAN, X-band satellite communication, point-to-point wireless applications, ITU band, military satellite communication, television broadcasting, and military land and airborne systems.

Throughput Optimized Non-Contiguous Wideband Spectrum Sensing via Online Learning and Sub-Nyquist Sampling

In this letter, we consider non-contiguous wideband spectrum sensing (WSS) using the sub-Nyquist sampling approach. Compared to contiguous WSS which senses the entire spectrum, non-contiguous WSS has an additional task of determining the number and location of frequency bands for digitization and sensing. Since throughput (i.e., the number of sensed vacant bands) increases while the probability of successful sensing decreases with a decrease in the sparsity of digitized bands, we develop exploration–exploitation-based online learning algorithm to learn the spectrum statistics. We provide a lower bound on the number of time slots required to learn spectrum statistics after which the proposed algorithm intelligently selects a maximum possible number of frequency bands which are more likely to be vacant and hence, it is named as throughput optimized non-contiguous WSS. Simulation and experimental results using USRP testbed validate the efficacy of the proposed approach compared to the Myopic approach which has prior knowledge of spectrum statistics.

Nonlinear Distortion Noise and Linear Attenuation in MIMO Systems—Theory and Application to Multiband Transmitters

Nonlinear static multiple-input multiple-output (MIMO) systems are analyzed. The matrix formulation of Bussgang's theorem for complex Gaussian signals is rederived and put in the context of the multivariate cumulant series expansion. The attenuation matrix is a function of the input signals’ covariance and the covariance of the input and output signals. The covariance of the distortion noise is in addition a function of the output signal's covariance. The effect of the observation bandwidth is discussed. Models of concurrent multiband transmitters are analyzed. For a transmitter with dual non-contiguous bands expressions for the normalized mean square error (NMSE) vs input signal power are derived for uncorrelated, partially correlated, and correlated input signals. A transmitter with arbitrary number of non-contiguous bands is analysed for correlated and uncorrelated signals. In an example, the NMSE is higher when the input signals are correlated than when they are uncorrelated for the same input signal power and it increases with the number of frequency bands. A concurrent dual band amplifier with contiguous bands is analyzed; in this case the NMSE depends on the bandwidth of the aggregated signal.